Improving hip fracture risk prediction based on femoral strength

Hip fractures are a major health concern for the elderly in modern societies, as they tend to lead to the loss of independence and high rate of death after fracture. With considerable and growing socio-economic burden associated with hip fractures due to ageing population, accurate risk assessment and effective intervention are much needed for preventive care.

Current clinical standard for assessing hip fracture risks relies on areal-bone-mineral-density (aBMD) measurements derived from dual energy X-ray images. However, aBMD lacks the required sensitivity and specificity for accurately identifying high-risk elderly. An alternative approach for assessing risk is to predict thigh bone strength based on computer models. However, such predictions have to date only shown marginal or no improvement in assessing hip fracture risk compared to aBMD.

Using data from the AGES Reykjavik study cohort, researchers from Future Health Technologies, ETH-Zurich, University of Iceland, and the Icelandic Heart Association conducted a external page study on hip fracture risk. They compared the ability of aBMD and predicted thigh bone strength in terms of assessing risk, and analysed the influence of different modelling techniques on the accuracy of thigh bone strength predictions and risk classification.

This is the first study, with large number of subjects, to assess thigh bone strength predictions using different loading conditions and material models for modelling the mechanical response of thigh bones under impact. Findings support the use of predicted thigh bone strength as a hip fracture classifier and suggest that modelling bone with non-linear mechanical properties and an alignment of thigh bone with low internal rotation and adduction might be most suitable for hip fracture risk assessment.

Researchers from the Future Health Technologies programme at the Singapore-ETH Centre include Dr Navrag Singh, Prof. William Taylor, Prof. Stephen Ferguson, and PD Dr Benedikt Helgason, who are part of the Early Detection of Health Risks and Prevention research module.